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논문 기본 정보
- 자료유형
- 학술저널
- 저자정보
- 저널정보
- 원광대학교 기초자연과학연구소 ANNALS OF FUZZY MATHEMATICS AND INFORMATICS ANNALS OF FUZZY MATHEMATICS AND INFORMATICS 제18권 제3호
- 발행연도
- 2019.1
- 수록면
- 273 - 284 (12page)
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초록· 키워드
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Information entropies have been widely applied in constructing heuristic attribute reduction. However, little attention has been paid to the information entropies for dynamic information systems with varying object set. In this paper, we present an incremental approach to update conditional complementary entropy for dynamic information systems with varying objects. Based on the new incremental formulas, we develop an incremental attribute reduction algorithm for decision table with varying object set. By a numerical experiment, we express the efficiency of the new method.
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참고문헌 (26)
참고문헌 신청
W. Bang / 1999 / New incremental learning algorithm in the framework of rough set theory / International Journal of Fuzzy Systems 1:25~36
C. G. Bai / 2016 / Complex investment decisions using rough set and fuzzy c-means: an example of investment in green supply chains / Eur. J. Oper. Res 248:507~521
T. Beaubouef / 1998 / Information-theoretic measures of uncertainty for rough sets and rough relational databases / Inform. Sci 109:535~563
I. Duentsch / 1998 / Uncertainty measures of rough set prediction / Arti cial Intelligence 106:109~137
J. H. Dai / 2013 / Attribute selction based on a new conditonal entropy for incomplete decision systems / Knowledge-Based Systems 39:207~213
C. G. Bai / 2016 / Complex investment decisions using rough set and fuzzy c-means: an example of investment in green supply chains / Eur. J. Oper. Res 248:507~521
T. Beaubouef / 1998 / Information-theoretic measures of uncertainty for rough sets and rough relational databases / Inform. Sci 109:535~563
I. Duentsch / 1998 / Uncertainty measures of rough set prediction / Arti cial Intelligence 106:109~137
J. H. Dai / 2013 / Attribute selction based on a new conditonal entropy for incomplete decision systems / Knowledge-Based Systems 39:207~213
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